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Persistent link: https://www.econbiz.de/10010234667
This paper proposes a new combined semiparametric estimator of the conditional variance that takes the product of a parametric estimator and a nonparametric estimator based on machine learning. A popular kernel-based machine learning algorithm, known as the kernel-regularized least squares...
Persistent link: https://www.econbiz.de/10012814196
Since 2009, stock markets have resided in a long bull market regime. Passive investment strategies have succeeded during this low-volatility growth period. From 2018 on, however, there was a transition into a more volatile market environment interspersed by corrections increasing in amplitude...
Persistent link: https://www.econbiz.de/10012419688
Monitoring economic conditions in real time, or nowcasting, is among the key tasks routinely performed by economists. Nowcasting entails some key challenges, which also characterise modern Big Data analytics, often referred to as the three "Vs": the large number of time series continuously...
Persistent link: https://www.econbiz.de/10012259379
forecasting. Economic forecasting is made difficult by economic complexity, which implies non-linearities (multiple interactions … the algorithm in forecasting GDP growth 3- to 12-months ahead is assessed through simulations in pseudo-real-time for six …
Persistent link: https://www.econbiz.de/10012203223
. Forecasting from such a model assuming "no structural break" and "correct model" is tantamount to ignoring important aspects of …) a random walk model. Optimal IC approach, though computational intensive, outperforms in forecasting next period …
Persistent link: https://www.econbiz.de/10012040055
Forecasting volatility models typically rely on either daily or high frequency (HF) data and the choice between these … these two family forecasting-volatility models, comparing their performance (in terms of Value at Risk, VaR) under the …
Persistent link: https://www.econbiz.de/10012958968
economies’ per capita income levels tend to move at a faster rate than that of developed economies. For forecasting, it uses the …
Persistent link: https://www.econbiz.de/10013216161
The multi-fractal analysis has been applied to investigate various stylized facts of the financial market including market efficiency, financial crisis, risk evaluation and crash prediction. This paper examines the daily return series of stock index of NASDAQ stock exchange. Also, in this study,...
Persistent link: https://www.econbiz.de/10013273743
Forecasting volatility models typically rely on either daily or high frequency (HF) data and the choice between these … these two family forecasting-volatility models, comparing their performance (in terms of Value at Risk, VaR) under the …
Persistent link: https://www.econbiz.de/10011674479